Browse skills

Evaluates question answering models using a provided dataset, generating performance metrics and identifying areas for improvement.

Aspire helps you refine prompts iteratively by suggesting improvements, boosting your chances of getting desired AI outputs and saving time.

Provides constructive design feedback, identifying usability issues and suggesting improvements based on established principles.

Analyzes workflows, identifies bottlenecks, and suggests data-driven improvements to boost efficiency and reduce operational costs.

Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/repo

Analyzes WordPress site speed, identifies optimization opportunities, and suggests actionable performance improvements.

obra's receiving-code-review analyzes pull requests, identifying potential bugs, style issues, and suggesting improvements for testers.

Captures agent learnings, errors, and corrections to enable continuous improvement. Logs to structured markdown files for review and pattern detection.

This skill analyzes code changes to highlight potential issues and improvements, boosting development efficiency and reducing bugs.

Analyzes backend code for bugs, inefficiencies, and style violations, suggesting improvements aligned with best practices.

Feedback Mastery helps refine your prompts for optimal AI responses by analyzing and suggesting improvements – boosting output quality & efficiency.

Identifies recurring workflow patterns in data to suggest process improvements and automation opportunities.

Identifies potential dbt transformation improvements like model duplication, unused columns, and inefficient logic.

This skill analyzes a website’s structure to identify potential improvements for user experience and SEO optimization, boosting its effectiveness.

Automatically drafts clear, concise postmortems from incident data, highlighting root causes and actionable improvements.

Analyzes complex SQL queries, identifies performance bottlenecks, and suggests optimized Prisma schema & query improvements.

Analyzes Linkerd service mesh configurations to suggest improvements based on established best practices and common patterns.

Event Continuous Improvement — provides AI agent assistance for software development workflows.

Enforces consistent code style by automatically suggesting improvements based on established coding standards, boosting readability and collaboration.

Automates Python/Node.js backend code reviews, identifying bugs, style issues, and suggesting performance improvements.

Automates Python backend code reviews, identifying potential bugs, style issues, and suggesting improvements using Llama 2 expertise.

Automates backend code improvements – simplifying logic, enhancing readability, and optimizing performance based on best practices.

Applies proven software engineering & agile principles to guide agent design, development, and iterative improvement.

Supercent-io's agent-evaluation assesses agent performance against defined metrics, providing actionable insights for improvement.